As part of his PhD program, Daniel Plews and supervisor Prof Paul Laursen performed an in-depth case study on two elite triathletes during two and a half months of preparation for a national level Olympic distance event.

This study differs from many others that we have summarized in two respects:

It is a very detailed examination of the response to carefully planned training in elite athletes who are 100% focused on winning national & international events

It provides a contrast between training that was effective in delivering the required performance on the day vs a situation where the athlete became non-functionally overreached (NFOR) and required unplanned time out in order to recover.

It’s also important to point out that this was an observational study, so although lots of data was recorded, no attempt was made to use it to modify training at the time of the study.

What did they do?

Both triathletes (one male, one female) trained as normal (20-25 hrs/week), whilst having the following data recorded daily:

HRV at morning wake (LnRMSSD)

Resting HR (same time as HRV)

Psychometric (subjective) indices:

Sleep quality

Fatigue

Muscle soreness

Stress

Training load (measured as training hours per day)

The only modification to the planned training was done via an alert to the coach when any of the subjective markers was below 3 on a 6 point scale.

What did they find?

It won’t come as a surprise to anyone who has trained regularly with HRV that whilst the HRV of the (male) athlete who performed well in competition maintained a very high average level throughout (equivalent to >100 on the ithlete scale), whilst the female athlete that became non-functionally overreached had a declining HRV well before the race, which she could not even finish on the day. Although she also started around 100 on the ithlete scale, a week before the event she was down to about 80, which further reduced to 73 on the day of the event.

A rolling 7 day HRV average (equivalent to the ithlete blue baseline) was also calculated and this showed a strong downward trend in the case of the overreached athlete toward the event, which then headed upwards during a period of enforced rest afterwards.

The coefficient of variation, or variability, of the HRV itself also reduced as the female athlete became non-functionally overreached – an observation that we will return to in the next section.

Resting heart rates.

In the case of the well-trained athlete, this decreased by 1 bpm every 3 weeks, whereas the overreached athlete had a 3 bpm increase per week.

Psychometric (subjective) indexes.

The only one that showed a trend was sleep quality, which decreased in the overreached athlete leading up to the event. There was some suggestion that since the athletes knew a low score would alert the coach, these low scores were not used, and were not therefore an accurate record.

What does it mean?

This is a well-conducted study providing a lot of detail, with a number of very useful observations & recommendations for using HRV as a training tool at the elite level:

HRV is a more sensitive and objective marker of potential non-functional overreaching and overtraining than either resting heart rate, or the most commonly used technique, psychometric (subjective) indicators. It’s hard to get elite and professional athletes to be honest when recording their sensations as they know it can have consequences for their training and selection

Due to a relatively high coefficient of variation, isolated (e.g. once a week) HRV measures can give misleading results, and this may be the reason that previous studies have come to different conclusions about the value of HRV to detect overreaching. Daily values (at least 3/4 per week) over extended periods are needed to provide sufficient data.

A 7-day rolling average of daily HRV is suggested to be a good tool for detecting the onset of non-functional overreaching. Trends in this rolling average can be used to create alerts that the current training program is too hard or intensive and that recovery needs to be increased.

As an example, if we overlay the HRV chart of the overreached athlete with the Week change and Month change indicators used in ithlete (both of which are based on the 7-day rolling average), we would see that a red warning would have been triggered for both on day 30. This is several days in advance of the post-study diagnosis of NFOR on day 37, and might have provided sufficient warning for training to be reduced and NFOR avoided. By contrast, these indications would not have been triggered at all for the other athlete who trained effectively and performed very well. The 7-day rolling average would also have helped identify when the overreached athlete was ready to return to training, as it would have given a green Month change on day 73.

As the athlete became overreached, the day-to-day variation in HRV also reduced. When training is working effectively, training load (stress) is sufficient to depress HRV for a short while, and then HRV rebounds during recovery to baseline, or even above, indicating super-compensation. A healthy pattern of HRV may be a relatively high variation of troughs and peaks caused by training (rather than lifestyle) stresses.

The authors pointed out the presence of saturation effects of HRV in the supine (lying down) position, which may make resting HR rather than HRV a better predictor of changes of fitness in this position, especially in elite athletes with very low resting HR. That’s why we recommend endurance athletes with very low resting heart rate perform their ithlete measurements standing.

Finally, the authors conclude that daily readings of HRV, with analysis of the variations and trends in the 7-day rolling average could be a sensitive indicator of the effectiveness of training at the elite level.

Original article

2 Comments

chris
on June 9, 2015 at 4:22 am

HI Simon

Here are my last 7 days HRV morning readings
I was surprised by days 5 and 6, but noted i took this readings after a weekend off training, but also much later in the morning 8.30am as opposed to my usual between 5 and 6 am prior to riding measurement
Will the time of day account for the rise in HRV?

Chris, I’m no expert, and not knowing your activities specifically, I would think that the combo of taking time off, and what I assume was more sleep (2.5-3.5 more hours a night, and you weren’t going to bed later) would be enough to account for the HRV increase. If that were my data, I’d want to consider increasing how long I regularly sleep and incorporate ways to balance my training to allow more recovery during the week, whether that be cross training, active recovery, complete rest, etc.